Exploiting 3D variational autoencoders for interactive vehicle design

Sneha Saha, Leandro Minku, Xin Yao, Bernard Sendhoff, Stefan Menzel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

In automotive digital development, 3D prototype creation is a team effort of designers and engineers, each contributing with ideas and technical evaluations through means of computer simulations. To support the team in the 3D design ideation and exploration task, we propose an interactive design system for assisted design explorations and faster performance estimations. We utilize the advantage of deep learning-based autoencoders to create a low-dimensional latent manifold of 3D designs, which is utilized within an interactive user interface to guide and strengthen the decision-making process.
Original languageEnglish
Title of host publicationDESIGN2022
PublisherCambridge University Press
Pages1747-1756
Number of pages10
Volume2
DOIs
Publication statusPublished - 26 May 2022
EventDESIGN 2022: 17th International Design Conference - Online, Croatia
Duration: 23 May 202226 May 2022

Publication series

NameProceedings of the Design Society

Conference

ConferenceDESIGN 2022
Country/TerritoryCroatia
Period23/05/2226/05/22

Bibliographical note

Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 766186 (ECOLE).

Publisher Copyright:
© The Author(s), 2022.

Keywords

  • data-driven design
  • collaborative design
  • 3D modelling

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